Category: Uncategorized

  • EMR queries for D2D – EMR Data Quality: Coded Diagnosis – Diabetes

    The EMR queries below were  developed by QIDSS and the EMR Communities of Practice to help you extract data for submission to D2D.

    Telus PS Accuro Nightingale OSCAR P&P

     

    NOTE: All queries are tested and validated prior to release. However, changes that take place after the queries are released may affect how accurate they are. Such changes could include EMR software updates, new medications, and changes to standard clinical definitions. They may result in false positives, that is, patients being flagged who do not have the specified condition. They may also result in false negatives, that is, patients not being flagged who do have the condition. Queries are also limited by the quality of your EMR data.

     

    Telus PS 

    The D2D EMR Data Quality Diabetes Coded v1 searches (.srx files) will extract data neccessary to calculate the percent of patients with diabetes whose diagnosis is recorded with a code in the appropriate place in the EMR. Save these searches to your desktop and import into your EMR. You might need the help of your QIDSS, IT staff or other person who usually run queries in your EMR. This guide provides screenshots of the searches along with instructions on how to import the searches into your EMR. Share you challenges and successes with the Telus PS CoP or contact us for more information.

    Accuro 

    Please find the D2D EMR Data Quality DM Coded v1 numerator and denominator queries on Publisher. You might need the help of your QIDSS, IT staff or any other person who usually run queries in your EMR. Share you challenges and successes with the Accuro CoP or contact us for more information.

    Nightingale 

    The D2D EMR data quality diabetes coded denominator query based on the case definition developed CPCSSN has proven difficult to build. Please contact us if you have a query for Nightingale that you’d like to share or if you have any suggestions for this work.

    OSCAR 

    Two sets of queries were created as a result of query run time issues. The following set of queries search for diabetic patients for all physicians. If you experience excessive query run time you can use the queries that run for each physician. Download either set of  queries to your computer and import into your EMR. You might need the help of your QIDSS, IT staff or any other person who usually run queries in your EMR. Share your challenges and successes with the OSCAR CoP or contact us for more information.

    P&P 

    The D2D EMR Data Quality Diabetes Coded query is currently under development. Please contact us if you have a query for P&P that you’d like to share or if you have any suggestions for this work.

  • EMR queries for D2D – EMR Data Quality: Smoking Status Complete

    Please find below EMR queries developed by QIDSS and the EMR Communities of Practice that will help you extract data for submission to D2D.

    Telus PS Accuro Nightingale OSCAR P&P

     

    NOTE: All queries are tested and validated prior to release. However, changes that take place after the queries are released may affect how accurate they are. Such changes could include EMR software updates, new medications, and changes to standard clinical definitions. They may result in false positives, that is, patients being flagged who do not have the specified condition. They may also result in false negatives, that is, patients not being flagged who do have the condition. Queries are also limited by the quality of your EMR data.

      Once you have tried running these queries consider sharing your challenges and success stories with your EMR CoP or with us so that others can benefit from improved and shared solutions!

    Telus PS (Note – There are issues with queries developed in previous versions of PS. We are in the process of updating the queries and will be available at the launch of D2D (August 21, 2017)

    The D2D EMR Data Quality Smoking Status v1.1.1 searches (.srx files) will extract data for the numerator and denominator for all patients (>=12 yrs) who have smoking status documented in the risk factors module. Save these searches to your desktop and import into your EMR. You might need the help of your QIDSS, IT staff or other person who usually run queries in your EMR. Instructions on how to import the searches into your EMR can be found in this guide. Share you challenges and successes with the Telus PS CoP or contact us for more information.

    Accuro 

    Please find the D2D EMR Data Quality Smoking Status v1 numerator and denominator queries on Publisher. Query criteria and instructions on how to generate rate data for the smoking status complete measure can be found in this guide. You might need the help of your QIDSS, IT staff or any other person who usually run queries in your EMR. Share you challenges and successes with the Accuro CoP or contact us for more information.

    Nightingale 

    Instructions on how to build and run a query in Data Miner to generate data for the smoking status complete measure can be found in this guide. Contact us to share you challenges and successes.

    OSCAR 

    Download the D2D EMR Data Quality Smoking Status v1 query to your computer and import into your EMR. You might need the help of your QIDSS, IT staff or any other person who usually run queries in your EMR. Share you challenges and successes with the OSCAR CoP or contact us for more information.

    P&P 

    The P&P Smoking Status Query v1 file (.dat file) includes the numerator and denominator queries that will help you generate data for all patients >=12 yrs old with smoking status documented in Risk Factors. The data field used in the numerator query is a “learning field” and may need to be customized depending on how your team documents smoking status. You might need the help of your QIDSS, IT staff or other person who usually run queries in your EMR to import and run this query. Share your challenges and successes with the P&P CoP or contact us for more information.

  • EMR queries for D2D – EMR Data Quality: Colorectal and Cervical Cancer Screening

    The EMR queries were developed by QIDSS and the EMR Communities of Practice to help you extract data for submission to D2D.

    Telus PS Accuro Nightingale OSCAR P&P

     

    NOTE: All queries are tested and validated prior to release. However, changes that take place after the queries are released may affect how accurate they are. Such changes could include EMR software updates, new medications, and changes to standard clinical definitions. They may result in false positives, that is, patients being flagged who do not have the specified condition. They may also result in false negatives, that is, patients not being flagged who do have the condition. Queries are also limited by the quality of your EMR data. 

      Remember that the cancer screening rates are for data quality purposes only. They are NOT intended as measures of performance of cancer screening. Once the EMR rates are determined you can compare them to the CCO Screening Activity Report (SAR) rates. The results will then be rolled up into the EMR Data Quality indicator. Teams are encouraged to use these results to discuss ways of standardizing data entry and cleaning up the EMR accordingly, as next steps in the QI process. You may have your own queries and criteria for local cancer screening initiatives. The queries presented below could be used to replace them if you like, but we cannot adjust the criteria here to make it more “useful” to people in the field given the purpose of the indicators to reflect data quality and as such, the need to match the SAR criteria as closely as possible. Once you have tried running these queries pleas consider sharing your challenges and successes with your EMR CoP or improve@afhto.ca.

    Telus PS 

    The D2D EMR Data Quality Cancer Screening v2 searches (.srx files) will extract data for the for up-to-date colorectal and cervical cancer screening rates. Save these searches to your desktop and import into your EMR. You might need the help of your QIDSS, IT staff or other person who usually run queries in your EMR. Instructions on how to import the searches into your EMR can be found in this guide, along with screenshots of the searches. Share your challenges and successes with the Telus PS CoP or  contact us  if you have any questions.

    Accuro 

    The numerator and denominator queries, and instructions on how to calculate screening rates can be found in the Colorectal Screening guide and the Cervical Screening guide. You might need the help of your QIDSS, IT staff or any other person who usually run queries in your EMR. Share your challenges and successes with the Accuro CoP or contact us for more information.

    Nightingale 

    Cervical and colorectal cancer screening queries can be run in data miner as illustrated in this guide. After calculating your EMR/SAR ratio, you might consider using the Health Maintenance (HM) module to clean up your EMR. Share you experiences with the Nightingale CoP or contact us with any questions or concerns.

    OSCAR 

    Please download the D2D EMR Data Quality Cancer Screening v1 queries to your computer. Have a look at this guide for instructions on how to import the queries and screenshots – notice that a drop down menu allows you to select a specific physician depending on who you have a SAR report for. You might consider adding exclusion criteria to the queries to match the SAR criteria as closely as possible. Please contact us for more information and consider sharing your challenges and successes running the queries with the OSCAR CoP.

    P&P 

    The current HMP module in P&P does not match the SAR criteria so work continues to build a query that is not based on billing data. Please contact us if you have a cancer screening query for P&P that you’d like to share or if you have any suggestions for this work.

  • EMR queries for D2D – Patients served

    The EMR queries below were developed by QIDSS and the EMR Communities of Practice to help you prepare data for D2D submission.

    Telus PS Accuro Nightingale OSCAR P&P

     

    NOTE: All queries are tested and validated prior to release. However, changes that take place after the queries are released may affect how accurate they are. Such changes could include EMR software updates, new medications, and changes to standard clinical definitions. They may result in false positives, that is, patients being flagged who do not have the specified condition. They may also result in false negatives, that is, patients not being flagged who do have the condition. Queries are also limited by the quality of your EMR data. 

      This indicator is intended to reflect the ENTIRE patient population served by a team, not just those who are rostered to the team. The definition is “the number of unique patients with a visit (i.e. appointment) to anyone in the team in the last 3 years”. This definition will continue to evolve in subsequent iterations of D2D as EMRs are increasingly capable of recording other meaningful patient encounters (e.g. phone calls) in a way that the data can easily be extracted. For D2D 4.0 the technical limitations of data extraction from EMRs dictate that only in-person encounters can be included in the definition.

    Telus PS 

    The D2D- Patients Served v1 search looks at unique patients with an appointment in the last 3 years. Save the search to your desktop and import into your EMR. You might need the help of your QIDSS, IT staff or other person who usually runs queries in your EMR. Consider sharing your challenges and successes with the Telus PS CoP or contact us for more information.

    Accuro 

    Please download the D2D- Patients Served v1 query from the publisher. The query returns patients with an appointment in the last 3 years and filters out “no shows”. You may need the help of your QIDSS, IT staff or any other person who usually runs queries in your EMR. Consider sharing your challenges and successes with the Accuro CoP or contact us for more information.

    Nightingale 

    Please use this guide to extract data for the patients served indicator using data miner. If you have any questions or would like training on data miner, contact us for more information.

    OSCAR 

    Please save the D2D- Patients Served v1 query to your computer. Here is a guide for importing the query and using the report generated by the query. Consider sharing your challenges and successes running this query with the OSCAR CoP or contact us for more information.

    P&P 

    Thanks to efforts of the CoP an approach to accessing appointment data (i.e “date last seen”) has been programmed by the vendor. It’s called the Patient Utilization ReportThis guide will show you how to access the report in the EMR. Please connect with the P&P CoP or contact us for more information.

  • Optimizing Interprofessional Resources & Spreading Access to Teams: Case Study (2016)

    As government implements the vision of Patients First, the creation of sub-LHIN regions will enable a shift to a population-based approach to health care planning and delivery. It is hoped through these system-level changes patients will receive more timely access to, and better integration of, primary care, and better coordination and continuity of services. By looking at the needs of a defined population in sub regions, there is also opportunity to create more equitable access to care and to ensure appropriate care options are in place to meet community needs. Creating equitable access to team based primary care for those who would benefit Currently only 25-30% of Ontarians have access to team-based primary care. Evidence tells us with a team-based approach to primary care, patients experience more timely access to care, better care coordination and improved management of chronic diseases. The question is – How do we optimize the use of team resources to maximize access without causing undue stress on providers, unacceptable increases in wait times, and/or decreases in quality of care? In order to spread interdisciplinary team capacity more broadly in communities, careful consideration must be given to understanding population needs, making best use of existing resources, and ensuring sufficient resources to provide optimal access and quality of care. Case Study: Optimizing Interprofessional Resources & Spreading Access to Teams AFHTO, in partnership with the Osborne Group, has prepared a case study for AFHTO members which looks at how two Family Health Teams (East GTA FHT and Guelph FHT) have expanded access in their community by providing programs and services to people who were not rostered to the FHT physicians. The case study may help inform the optimal use of FHT/NPLC skills and resources and stimulate conversations amongst leadership on how we can get the best value for investment in team-based care. The case study is well aligned with AFHTO’s literature review and position paper “Optimizing value of and access to team-based primary care.” Sufficient capacity must be developed to spread access to all Ontarians Team-based primary care is already making a HUGE contribution in moving toward the vision expressed in Patients First. As we navigate through the reforms introduced we see the potential for much greater attention to the role and importance of primary care. It also reinforces the need – and creates possible mechanisms – for investment to expand team-based primary care and deliver on our membership’s vision that all Ontarians will have access to high-quality, comprehensive, interprofessional primary care. Learning from your peers: additional case studies AFHO has developed a series of case studies for our members to share the experience of colleagues on topics identified as being important to you:

  • Optimizing Interprofessional Resources & Spreading Access to Teams: Case Study (2016)

    As government implements the vision of Patients First, the creation of sub-LHIN regions will enable a shift to a population-based approach to health care planning and delivery. It is hoped through these system-level changes patients will receive more timely access to, and better integration of, primary care, and better coordination and continuity of services. By looking at the needs of a defined population in sub regions, there is also opportunity to create more equitable access to care and to ensure appropriate care options are in place to meet community needs.

    Creating equitable access to team based primary care for those who would benefit
    Currently only 25-30% of Ontarians have access to team-based primary care. Evidence tells us with a team-based approach to primary care, patients experience more timely access to care, better care coordination and improved management of chronic diseases. The question is – How do we optimize the use of team resources to maximize access without causing undue stress on providers, unacceptable increases in wait times, and/or decreases in quality of care?

    In order to spread interdisciplinary team capacity more broadly in communities, careful consideration must be given to understanding population needs, making best use of existing resources, and ensuring sufficient resources to provide optimal access and quality of care.

    Case Study: Optimizing Interprofessional Resources & Spreading Access to Teams
    AFHTO, in partnership with the Osborne Group, has prepared a case study for AFHTO members which looks at how two Family Health Teams (East GTA FHT and Guelph FHT) have expanded access in their community by providing programs and services to people who were not rostered to the FHT physicians. The case study may help inform the optimal use of FHT/NPLC skills and resources and stimulate conversations amongst leadership on how we can get the best value for investment in team-based care.

    The case study is well aligned with AFHTO’s literature review and position paper “Optimizing value of and access to team-based primary care.”

    Sufficient capacity must be developed to spread access to all Ontarians
    Team-based primary care is already making a HUGE contribution in moving toward the vision expressed in Patients First. As we navigate through the reforms introduced we see the potential for much greater attention to the role and importance of primary care. It also reinforces the need – and creates possible mechanisms – for investment to expand team-based primary care and deliver on our membership’s vision that all Ontarians will have access to high-quality, comprehensive, interprofessional primary care.

    Learning from your peers: additional case studies
    AFHO has developed a series of case studies for our members to share the experience of colleagues on topics identified as being important to you:

  • Data to Decisions eBulletin #39: A new exploratory indicator – follow-up after hospitalization

    A better way to track follow-up after hospitalization: Primary care providers know the importance of following up with their patients after hospitalization and tracking how well they are doing that. Read on to learn how you and your team can contribute to the new exploratory D2D indicator and help AFHTO advocate for a better measure of how the entire team provides patient-centred follow-up after hospitalization. Data input toolkit now available to help you prepare your data for submission. D2D 4.0 submission platform opens August 11. New to D2D? Need a refresher? Register here for the webinar on August 11, 2015 from 2:00 to 3:00 pm (EST). Case Study – Building Collaboration and Increased Capacity through QIDS partnerships: This new resource illustrates and examines three different approaches to organizing QIDS partnerships along with challenges faced, enablers for success, and lessons learned. AFHTO measurement efforts capture widespread attention: People across Ontario and North America are keen to learn about the ground-breaking advances AFHTO members are making to meaningfully measure primary care. AFHTO is giving nine presentations at four major conferences, read more about recent and upcoming presentations. members

    Help spread the word about D2D – invite others to sign up for the eBulletin online. 

  • Exploratory Indicator: A better way to track follow-up after hospitalization

    Primary care providers know the importance of following up with their patients after hospitalization. They also know the importance of tracking how well they are doing with that. Read on for a description of a better measure of how the entire team provides follow-up after hospitalization.

    Definition of the new indicator for follow-up after hospitalization:

    The new indicator is defined as % of those discharges (any condition) where timely (within 48 hours) notification was received, for which follow-up was done (by any mode, any clinician) within 7 days of discharge. Note that this is a different definition from the Ministry of Health and Long-Term Care (MOHLTC) indicator available on the Health Data Branch (HDB) portal. Based on the input from AFHTO members, this new definition includes follow up by ANY member of the team by ANY method (e.g., phone or in-person visit).

    Why is a new definition needed?

    The definition above is a better reflection of how follow-up actually happens in primary care teams.  In-person visits with physicians are not required for many patients after they are discharged from hospital, especially if it was their own physician who just discharged them. However, many patients DO receive follow-up by a pharmacist to make sure all of their medications are in order or by a social worker to make sure they are adjusting to being home. Teams do this because it is what their patients want and need. It is also more efficient, freeing up physician appointment time. Unfortunately, as teams get increasingly good at this patient-centered, efficient approach to follow-up, their performance on the current MOHLTC indicator (which is based only on physician billing data) will paradoxically look worse. This is why a new definition is needed.

    We already track follow-up in a way that works for our team. Why should we change?

    Just as follow-up is important to primary care providers, it is important to MOHLTC as a measure of the quality of transitions in the healthcare system. Transitions are such an important focus that MOHLTC will continue to use whatever measures are available. The current measure has the advantage of being readily available for all primary care providers (i.e., not just AFHTO members). This is a non-negotiable characteristic for any system-level measure. MOHLTC does, however, recognize that the current measure may paradoxically indicate that transitions are getting worse as primary care providers become increasingly efficient at team-based care, with less physicians and more Interprofessional Health Providers (IHPs) providing follow-up care. D2D 2.0 illustrated that AFHTO members have developed many creative solutions for tracking follow-up in a meaningful way. These solutions undoubtedly are useful in ensuring good quality transitions within the team. However, it is not possible to make a strong argument for system change on the basis of a collection of different strategies in use at small numbers of teams. When AFHTO members can propose a consistent, unified approach, it is easier for system-level decision-makers to respond to our needs. AFHTO members can help themselves and the system by adopting the following consistent approach to measuring follow-up. This would help in the efforts to reframe, expand or even retire the current measure in favour of one that better reflects what does, could and should happen in team-based primary care.

    Why track follow-up if we don’t get hospitalization data?

    Tracking follow-up after hospitalization requires 2 bits of data: date of discharge from hospital, and date of follow-up by primary care provider. It is necessary for primary care providers to become proficient at tracking patient encounters with all members of the team in all modes (e.g., phone, in person), no matter what the state of hospital data-sharing is. In fact, better data about how much your team interacts with your patients in all ways is important data beyond follow up after hospitalization. For example, it is a good way to demonstrate the amount of care your team provides. It can also support arguments to reconsider the historic requirement that physicians can only bill in-person visits.  Both of these also require consistent approaches to measurement.

    What is the evidence that follow-up even really makes a difference?

    Recent analysis is showing that follow-up by a primary care physician within 7 days of discharge from hospital is associated with 68 fewer readmissions per 1000 patients. Follow links for more details:

    Who came up with the new definition? Were members and clinicians involved?

    Learnings from D2D 2.0 Exploratory indicator: 7-Day Follow up, along with feedback received from Clinical consultations for Strategic D2D indicators, were used to create a proposed indicator definition. This definition was subsequently recommended by the Indicator Working Group (IWG) to be included in the membership wide vote on D2D 4.0. The indicator definition was endorsed by a membership-wide vote, in which more than 240 members from at least 75 teams participated.

    How can our team be part of the new consistent, more meaningful measure for follow-up?

    We know from clinical consultations that clinicians already track phone-based discussions with their patients, usually in an unstructured, free-text kind of way in the EMR. We know from D2D 2.0 that some teams also specifically track follow-up visits (either by phone or in-person), in the EMR and outside of the EMR. It could be that your team has developed a process that works well at the local level. However, local solutions, however elegant, are not helping move the system towards a more meaningful way of understanding follow-up from a primary care team perspective. The following tools will help teams take a standardized, consistent approach that will make it easier to record and extract that data from the EMR. As noted above, it is the CONSISTENCY of recording and reporting follow-up that are the key to being able to influence system-level choices about this indicator.

    Why just phone encounters?

    Actually, it is important to track all encounters with patients. However, most EMRs are good at tracking in-person encounters, at least through the scheduling system. The gap remains in tracking discussions with patients that are not scheduled, in-person visits. Hence, our focus on improving our collective ability to consistently track phone encounters. Eventually, email encounters may also be considered; for now, the focus is on phone encounters as an easier place to start.

    But what about the hospitalization data?

    AFHTO continues to work with external partners including OntarioMD, local hospitals as well as the Ontario Hospital Association, eHealth Ontario, and LHINs to improve the flow of data from hospitals to primary care. In the meantime, teams are continuing their local efforts to get as much information as quickly as possible from their local hospitals. Teams can make progress in tracking all patient encounters with any provider (including phone) in a consistent way. This is important not only because the information is useful in itself but also to demonstrate to our external partners our commitment to a better solution and thus help expedite changes in their systems.

  • Building Collaboration: Case Study based on QIDS Partnerships

    Patients First calls for collaboration across subLHIN regions. It also calls for spreading measurement for quality improvement and performance monitoring. AFHTO members’ experience in building QIDS partnerships (about 150 AFHTO member organizations are actively involved) provides a foundation for both these objectives. These QIDS partnerships have been a critical ingredient in the advances AFHTO members are making to meaningfully measure primary care. This new resource – Building Collaboration and Increased Capacity through QIDS Partnerships – illustrates three different approaches to organizing these partnerships. It describes each approach and then examines all three to identify the challenges they faced, the enablers for success and the lessons learned. This knowledge, together with that gained from other types of partnerships AFHTO members have developed, can be applied to strengthen your QIDS partnership, evaluate existing partnerships (e.g. Health Links and other community programs) and help to broaden your reach into other areas of collaboration. Learning from your peers: additional case studies AFHTO has developed a series of case studies for our members to share the experience of colleagues on topics identified as being important to you:

  • Case Study: Learning about unionization from ten FHTs

    About 25 FHTs across the province have unionized workplaces. AFHTO, in partnership with the Osborne Group, has prepared a case study for AFHTO members which looks at the advice and learnings from 10 of these FHTs. Even with the anticipated increase in funding, compensation in primary care will remain below market comparators, and so the potential for further unionization remains. Primary care leaders may wish to think about how to prepare for the possibility of union organizing efforts in their FHT or NPLC. The case study documents motivators for union drives and what teams went through in the process of union certification, negotiation and managing in a unionized environment. Importantly, the experience of these 10 teams highlights both the challenges and possible benefits of working under a Collective Agreement. The case study may assist other FHTs/NPLCs as they contemplate the potential for, and the implications of, unionization in their own workplaces. Because of the sensitive nature of some of the information that was provided to us, we have not identified the FHTs by name. However, if any primary health care teams are interested in speaking directly to the Executive Directors or Boards of these FHTs, AFHTO will facilitate an introduction. Case Study: Unionization – The Experience of Ten Family Health Teams [PDF]

    Toward a Primary Care Recruitment and Retention Strategy for Ontario

    The increase in funding announced in the 2016 Ontario budget is a first step in a longer-term strategy to achieve greater equity in compensation within team based primary care. The AFHTO-AOHC-NPAO proposal remains our goal; on behalf of our members, AFHTO will continue to press for the full funding needed to make working in primary care attractive to recruit and retain competent staff in this sector. As for implementation of government’s 2016-17 commitment, approval letters for each FHT, NPLC, AHAC (and through the LHINs for CHCs) are in the final stages of ministry sign-off. We don’t know how long this will take, but hopefully will be “soon”. The funding will be retroactive to April 1, 2016.  Once funding letters are available and Ministry approvals are in place regarding the funding allocation, AFHTO (with MOHLTC participation) will hold technical briefings with EDs & Board Chairs.

    Learning from your peers: additional case studies

    AFHO has developed a series of case studies for our members to share the experience of colleagues on topics identified as being important to you: